Pandas Profiling Report

Dataset statistics

Number of variables	19
Number of observations	420768
Missing cells	3724
Missing cells (%)	< 0.1%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	61.0 MiB
Average record size in memory	152.0 B

Variable types

Numeric	16
Categorical	3

Warnings

`df_index` is highly correlated with `No` and 1 other fields	High correlation
`No` is highly correlated with `df_index` and 1 other fields	High correlation
`year` is highly correlated with `df_index` and 1 other fields	High correlation
`RAIN` is highly skewed (γ1 = 30.04363268)	Skewed
`df_index` is uniformly distributed	Uniform
`No` is uniformly distributed	Uniform
`station` is uniformly distributed	Uniform
`hour` has 17532 (4.2%) zeros	Zeros
`RAIN` has 403858 (96.0%) zeros	Zeros
`WSPM` has 11118 (2.6%) zeros	Zeros

Reproduction

Analysis started	2021-01-09 14:36:55.250010
Analysis finished	2021-01-09 14:38:28.424790
Duration	1 minute and 33.17 seconds
Software version	pandas-profiling v2.10.0
Download configuration	config.yaml

df_index
Real number (ℝ_≥0)

HIGH CORRELATION
UNIFORM

Distinct	35064
Distinct (%)	8.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	17531.5
Minimum	0
Maximum	35063
Zeros	12
Zeros (%)	< 0.1%
Memory size	3.2 MiB

Quantile statistics

Minimum	0
5-th percentile	1753
Q1	8765.75
median	17531.5
Q3	26297.25
95-th percentile	33310
Maximum	35063
Range	35063
Interquartile range (IQR)	17531.5

Descriptive statistics

Standard deviation	10122.11694
Coefficient of variation (CV)	0.5773674211
Kurtosis	-1.200000002
Mean	17531.5
Median Absolute Deviation (MAD)	8766
Skewness	0
Sum	7376694192
Variance	102457251.4
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	12	< 0.1%
17826	12	< 0.1%
15533	12	< 0.1%
9390	12	< 0.1%
11439	12	< 0.1%
33978	12	< 0.1%
21920	12	< 0.1%
23969	12	< 0.1%
19875	12	< 0.1%
4011	12	< 0.1%
Other values (35054)	420648	> 99.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	12	< 0.1%
1	12	< 0.1%
2	12	< 0.1%
3	12	< 0.1%
4	12	< 0.1%

Value	Count	Frequency (%)
35063	12	< 0.1%
35062	12	< 0.1%
35061	12	< 0.1%
35060	12	< 0.1%
35059	12	< 0.1%

No
Real number (ℝ_≥0)

HIGH CORRELATION
UNIFORM

Distinct	35064
Distinct (%)	8.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	17532.5
Minimum	1
Maximum	35064
Zeros	0
Zeros (%)	0.0%
Memory size	3.2 MiB

Quantile statistics

Minimum	1
5-th percentile	1754
Q1	8766.75
median	17532.5
Q3	26298.25
95-th percentile	33311
Maximum	35064
Range	35063
Interquartile range (IQR)	17531.5

Descriptive statistics

Standard deviation	10122.11694
Coefficient of variation (CV)	0.5773344899
Kurtosis	-1.200000002
Mean	17532.5
Median Absolute Deviation (MAD)	8766
Skewness	0
Sum	7377114960
Variance	102457251.4
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
2049	12	< 0.1%
19875	12	< 0.1%
9390	12	< 0.1%
11439	12	< 0.1%
33978	12	< 0.1%
21920	12	< 0.1%
23969	12	< 0.1%
17826	12	< 0.1%
30116	12	< 0.1%
14252	12	< 0.1%
Other values (35054)	420648	> 99.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	12	< 0.1%
2	12	< 0.1%
3	12	< 0.1%
4	12	< 0.1%
5	12	< 0.1%

Value	Count	Frequency (%)
35064	12	< 0.1%
35063	12	< 0.1%
35062	12	< 0.1%
35061	12	< 0.1%
35060	12	< 0.1%

year
Categorical

HIGH CORRELATION

Distinct	5
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	3.2 MiB

2016	105408
2014	105120
2015	105120
2013	88128
2017	16992

Length

Max length	4
Median length	4
Mean length	4
Min length	4

Characters and Unicode

Total characters	1683072
Distinct characters	8
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2013
2nd row	2013
3rd row	2013
4th row	2013
5th row	2013

Value	Count	Frequency (%)
2016	105408	25.1%
2014	105120	25.0%
2015	105120	25.0%
2013	88128	20.9%
2017	16992	4.0%

Histogram of lengths of the category

Value	Count	Frequency (%)
2016	105408	25.1%
2014	105120	25.0%
2015	105120	25.0%
2013	88128	20.9%
2017	16992	4.0%

Most occurring characters

Value	Count	Frequency (%)
2	420768	25.0%
0	420768	25.0%
1	420768	25.0%
6	105408	6.3%
4	105120	6.2%
5	105120	6.2%
3	88128	5.2%
7	16992	1.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	1683072	100.0%

Most frequent character per category

Value	Count	Frequency (%)
2	420768	25.0%
0	420768	25.0%
1	420768	25.0%
6	105408	6.3%
4	105120	6.2%
5	105120	6.2%
3	88128	5.2%
7	16992	1.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	1683072	100.0%

Most frequent character per script

Value	Count	Frequency (%)
2	420768	25.0%
0	420768	25.0%
1	420768	25.0%
6	105408	6.3%
4	105120	6.2%
5	105120	6.2%
3	88128	5.2%
7	16992	1.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1683072	100.0%

Most frequent character per block

Value	Count	Frequency (%)
2	420768	25.0%
0	420768	25.0%
1	420768	25.0%
6	105408	6.3%
4	105120	6.2%
5	105120	6.2%
3	88128	5.2%
7	16992	1.0%

month
Real number (ℝ_≥0)

Distinct	12
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	6.5229295
Minimum	1
Maximum	12
Zeros	0
Zeros (%)	0.0%
Memory size	3.2 MiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	4
median	7
Q3	10
95-th percentile	12
Maximum	12
Range	11
Interquartile range (IQR)	6

Descriptive statistics

Standard deviation	3.44870728
Coefficient of variation (CV)	0.5287052818
Kurtosis	-1.208056663
Mean	6.5229295
Median Absolute Deviation (MAD)	3
Skewness	-0.009293857222
Sum	2744640
Variance	11.8935819
Monotocity	Not monotonic

Histogram with fixed size bins (bins=12)

Value	Count	Frequency (%)
1	35712	8.5%
3	35712	8.5%
5	35712	8.5%
7	35712	8.5%
8	35712	8.5%
10	35712	8.5%
12	35712	8.5%
4	34560	8.2%
6	34560	8.2%
9	34560	8.2%
Other values (2)	67104	15.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	35712	8.5%
2	32544	7.7%
3	35712	8.5%
4	34560	8.2%
5	35712	8.5%

Value	Count	Frequency (%)
12	35712	8.5%
11	34560	8.2%
10	35712	8.5%
9	34560	8.2%
8	35712	8.5%

day
Real number (ℝ_≥0)

Distinct	31
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	15.72963723
Minimum	1
Maximum	31
Zeros	0
Zeros (%)	0.0%
Memory size	3.2 MiB

Quantile statistics

Minimum	1
5-th percentile	2
Q1	8
median	16
Q3	23
95-th percentile	29
Maximum	31
Range	30
Interquartile range (IQR)	15

Descriptive statistics

Standard deviation	8.800102498
Coefficient of variation (CV)	0.5594599778
Kurtosis	-1.194030263
Mean	15.72963723
Median Absolute Deviation (MAD)	8
Skewness	0.006759540549
Sum	6618528
Variance	77.44180397
Monotocity	Not monotonic

Histogram with fixed size bins (bins=31)

Value	Count	Frequency (%)
1	13824	3.3%
2	13824	3.3%
28	13824	3.3%
27	13824	3.3%
26	13824	3.3%
25	13824	3.3%
24	13824	3.3%
23	13824	3.3%
22	13824	3.3%
21	13824	3.3%
Other values (21)	282528	67.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	13824	3.3%
2	13824	3.3%
3	13824	3.3%
4	13824	3.3%
5	13824	3.3%

Value	Count	Frequency (%)
31	8064	1.9%
30	12672	3.0%
29	12960	3.1%
28	13824	3.3%
27	13824	3.3%

hour
Real number (ℝ_≥0)

ZEROS

Distinct	24
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	11.5
Minimum	0
Maximum	23
Zeros	17532
Zeros (%)	4.2%
Memory size	3.2 MiB

Quantile statistics

Minimum	0
5-th percentile	1
Q1	5.75
median	11.5
Q3	17.25
95-th percentile	22
Maximum	23
Range	23
Interquartile range (IQR)	11.5

Descriptive statistics

Standard deviation	6.922194778
Coefficient of variation (CV)	0.6019299807
Kurtosis	-1.204173963
Mean	11.5
Median Absolute Deviation (MAD)	6
Skewness	0
Sum	4838832
Variance	47.91678055
Monotocity	Not monotonic

Histogram with fixed size bins (bins=24)

Value	Count	Frequency (%)
0	17532	4.2%
1	17532	4.2%
22	17532	4.2%
21	17532	4.2%
20	17532	4.2%
19	17532	4.2%
18	17532	4.2%
17	17532	4.2%
16	17532	4.2%
15	17532	4.2%
Other values (14)	245448	58.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	17532	4.2%
1	17532	4.2%
2	17532	4.2%
3	17532	4.2%
4	17532	4.2%

Value	Count	Frequency (%)
23	17532	4.2%
22	17532	4.2%
21	17532	4.2%
20	17532	4.2%
19	17532	4.2%

PM2.5
Real number (ℝ_≥0)

Distinct	888
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	79.27848933
Minimum	2
Maximum	999
Zeros	0
Zeros (%)	0.0%
Memory size	3.2 MiB

Quantile statistics

Minimum	2
5-th percentile	6
Q1	21
median	55
Q3	109
95-th percentile	240
Maximum	999
Range	997
Interquartile range (IQR)	88

Descriptive statistics

Standard deviation	80.05679864
Coefficient of variation (CV)	1.009817408
Kurtosis	6.17192489
Mean	79.27848933
Median Absolute Deviation (MAD)	39
Skewness	2.047948852
Sum	33357851.4
Variance	6409.091009
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
55	11218	2.7%
3	8810	2.1%
10	7088	1.7%
9	6886	1.6%
8	6836	1.6%
11	6831	1.6%
12	6731	1.6%
7	6183	1.5%
13	6178	1.5%
14	6076	1.4%
Other values (878)	347931	82.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
2	17	< 0.1%
3	8810	2.1%
4	3476	0.8%
4.3	2	< 0.1%
4.4	1	< 0.1%

Value	Count	Frequency (%)
999	1	< 0.1%
957	1	< 0.1%
941	1	< 0.1%
898	1	< 0.1%
882	1	< 0.1%

PM10
Real number (ℝ_≥0)

Distinct	1084
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	104.2561932
Minimum	2
Maximum	999
Zeros	0
Zeros (%)	0.0%
Memory size	3.2 MiB

Quantile statistics

Minimum	2
5-th percentile	10
Q1	36
median	82
Q3	144
95-th percentile	278
Maximum	999
Range	997
Interquartile range (IQR)	108

Descriptive statistics

Standard deviation	91.10874488
Coefficient of variation (CV)	0.8738928795
Kurtosis	6.340266838
Mean	104.2561932
Median Absolute Deviation (MAD)	51
Skewness	1.908980906
Sum	43867669.9
Variance	8300.803394
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
82	8440	2.0%
6	4945	1.2%
18	3748	0.9%
5	3731	0.9%
14	3725	0.9%
16	3616	0.9%
17	3607	0.9%
13	3576	0.8%
20	3555	0.8%
15	3468	0.8%
Other values (1074)	378357	89.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
2	103	< 0.1%
3	726	0.2%
4	270	0.1%
5	3731	0.9%
5.4	2	< 0.1%

Value	Count	Frequency (%)
999	3	< 0.1%
995	1	< 0.1%
994	1	< 0.1%
993	1	< 0.1%
992	1	< 0.1%

SO2
Real number (ℝ_≥0)

Distinct	691
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	15.64150718
Minimum	0.2856
Maximum	500
Zeros	0
Zeros (%)	0.0%
Memory size	3.2 MiB

Quantile statistics

Minimum	0.2856
5-th percentile	2
Q1	3
median	7
Q3	19
95-th percentile	60
Maximum	500
Range	499.7144
Interquartile range (IQR)	16

Descriptive statistics

Standard deviation	21.45541881
Coefficient of variation (CV)	1.37169766
Kurtosis	14.54762913
Mean	15.64150718
Median Absolute Deviation (MAD)	5
Skewness	3.051065785
Sum	6581445.695
Variance	460.3349961
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
2	98557	23.4%
3	32784	7.8%
7	23410	5.6%
4	21716	5.2%
5	17964	4.3%
6	16567	3.9%
8	13348	3.2%
9	11559	2.7%
10	10651	2.5%
11	9362	2.2%
Other values (681)	164850	39.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0.2856	89	< 0.1%
0.5712	70	< 0.1%
0.8568	72	< 0.1%
1	3258	0.8%
1.1424	84	< 0.1%

Value	Count	Frequency (%)
500	3	< 0.1%
411	1	< 0.1%
341	1	< 0.1%
315	1	< 0.1%
314	1	< 0.1%

NO2
Real number (ℝ_≥0)

Distinct	1213
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	50.63858559
Minimum	1.0265
Maximum	290
Zeros	0
Zeros (%)	0.0%
Memory size	3.2 MiB

Quantile statistics

Minimum	1.0265
5-th percentile	8
Q1	24
median	45
Q3	70
95-th percentile	117
Maximum	290
Range	288.9735
Interquartile range (IQR)	46

Descriptive statistics

Standard deviation	34.61846291
Coefficient of variation (CV)	0.6836380302
Kurtosis	1.328475761
Mean	50.63858559
Median Absolute Deviation (MAD)	23
Skewness	1.065507904
Sum	21307096.38
Variance	1198.437974
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
50.63858559	12116	2.9%
16	5799	1.4%
22	5755	1.4%
20	5718	1.4%
17	5690	1.4%
18	5676	1.3%
21	5608	1.3%
26	5601	1.3%
14	5595	1.3%
19	5576	1.3%
Other values (1203)	357634	85.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1.0265	3	< 0.1%
1.2318	2	< 0.1%
1.4371	2	< 0.1%
1.6424	3	< 0.1%
1.8477	1	< 0.1%

Value	Count	Frequency (%)
290	1	< 0.1%
285	1	< 0.1%
280	1	< 0.1%
277	2	< 0.1%
276	1	< 0.1%

CO
Real number (ℝ_≥0)

Distinct	132
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	1214.493362
Minimum	100
Maximum	10000
Zeros	0
Zeros (%)	0.0%
Memory size	3.2 MiB

Quantile statistics

Minimum	100
5-th percentile	200
Q1	500
median	900
Q3	1500
95-th percentile	3400
Maximum	10000
Range	9900
Interquartile range (IQR)	1000

Descriptive statistics

Standard deviation	1133.542988
Coefficient of variation (CV)	0.9333463839
Kurtosis	10.00574467
Mean	1214.493362
Median Absolute Deviation (MAD)	400
Skewness	2.661900608
Sum	511019943
Variance	1284919.705
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
900	41931	10.0%
300	32308	7.7%
400	31275	7.4%
500	29171	6.9%
600	28035	6.7%
700	26488	6.3%
800	23370	5.6%
1000	19462	4.6%
200	18434	4.4%
1100	17414	4.1%
Other values (122)	152880	36.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
100	5695	1.4%
150	1	< 0.1%
200	18434	4.4%
300	32308	7.7%
350	1	< 0.1%

Value	Count	Frequency (%)
10000	56	< 0.1%
9900	30	< 0.1%
9800	31	< 0.1%
9700	29	< 0.1%
9600	28	< 0.1%

O3
Real number (ℝ_≥0)

Distinct	1598
Distinct (%)	0.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	56.98187409
Minimum	0.2142
Maximum	1071
Zeros	0
Zeros (%)	0.0%
Memory size	3.2 MiB

Quantile statistics

Minimum	0.2142
5-th percentile	2
Q1	12
median	45
Q3	80
95-th percentile	175
Maximum	1071
Range	1070.7858
Interquartile range (IQR)	68

Descriptive statistics

Standard deviation	55.80241254
Coefficient of variation (CV)	0.9793011099
Kurtosis	6.584750256
Mean	56.98187409
Median Absolute Deviation (MAD)	34
Skewness	1.703768067
Sum	23976149.2
Variance	3113.909245
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
2	42327	10.1%
45	16018	3.8%
3	8720	2.1%
4	8049	1.9%
1	6958	1.7%
5	6462	1.5%
6	6001	1.4%
8	4997	1.2%
7	4949	1.2%
9	4238	1.0%
Other values (1588)	312049	74.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0.2142	134	< 0.1%
0.4284	119	< 0.1%
0.6426	118	< 0.1%
0.8568	120	< 0.1%
1	6958	1.7%

Value	Count	Frequency (%)
1071	14	< 0.1%
1050	1	< 0.1%
1026	1	< 0.1%
674	1	< 0.1%
673	1	< 0.1%

TEMP
Real number (ℝ)

Distinct	2034
Distinct (%)	0.5%
Missing	398
Missing (%)	0.1%
Infinite	0
Infinite (%)	0.0%

Mean	13.53897583
Minimum	-19.9
Maximum	41.6
Zeros	2739
Zeros (%)	0.7%
Memory size	3.2 MiB

Quantile statistics

Minimum	-19.9
5-th percentile	-4.2
Q1	3.1
median	14.5
Q3	23.3
95-th percentile	30.6
Maximum	41.6
Range	61.5
Interquartile range (IQR)	20.2

Descriptive statistics

Standard deviation	11.43613941
Coefficient of variation (CV)	0.8446827551
Kurtosis	-1.143301395
Mean	13.53897583
Median Absolute Deviation (MAD)	9.8
Skewness	-0.1042674902
Sum	5691379.271
Variance	130.7852846
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
3	3414	0.8%
1	2903	0.7%
0	2739	0.7%
2	2687	0.6%
-1	2562	0.6%
-2	2396	0.6%
-4	1907	0.5%
4	1830	0.4%
5	1748	0.4%
-5	1662	0.4%
Other values (2024)	396522	94.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-19.9	1	< 0.1%
-19.7	1	< 0.1%
-19.5	1	< 0.1%
-18.9	1	< 0.1%
-18.7	1	< 0.1%

Value	Count	Frequency (%)
41.6	1	< 0.1%
41.4	2	< 0.1%
41.1	3	< 0.1%
41	2	< 0.1%
40.9	1	< 0.1%

PRES
Real number (ℝ_≥0)

Distinct	726
Distinct (%)	0.2%
Missing	393
Missing (%)	0.1%
Infinite	0
Infinite (%)	0.0%

Mean	1010.746982
Minimum	982.4
Maximum	1042.8
Zeros	0
Zeros (%)	0.0%
Memory size	3.2 MiB

Quantile statistics

Minimum	982.4
5-th percentile	994.7
Q1	1002.3
median	1010.4
Q3	1019
95-th percentile	1027.9
Maximum	1042.8
Range	60.4
Interquartile range (IQR)	16.7

Descriptive statistics

Standard deviation	10.47405475
Coefficient of variation (CV)	0.01036268714
Kurtosis	-0.8292032059
Mean	1010.746982
Median Absolute Deviation (MAD)	8.4
Skewness	0.1063136066
Sum	424892762.6
Variance	109.7058229
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1019	2948	0.7%
1021	2932	0.7%
1018	2868	0.7%
1020	2862	0.7%
1023	2838	0.7%
1022	2746	0.7%
1017	2707	0.6%
1016	2702	0.6%
1015	2700	0.6%
1024	2653	0.6%
Other values (716)	392419	93.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
982.4	2	< 0.1%
982.7	2	< 0.1%
982.8	3	< 0.1%
982.9	2	< 0.1%
983	4	< 0.1%

Value	Count	Frequency (%)
1042.8	2	< 0.1%
1042.4	1	< 0.1%
1042.3	2	< 0.1%
1042.2	1	< 0.1%
1042	11	< 0.1%

DEWP
Real number (ℝ)

Distinct	645
Distinct (%)	0.2%
Missing	403
Missing (%)	0.1%
Infinite	0
Infinite (%)	0.0%

Mean	2.490822024
Minimum	-43.4
Maximum	29.1
Zeros	832
Zeros (%)	0.2%
Memory size	3.2 MiB

Quantile statistics

Minimum	-43.4
5-th percentile	-19.9
Q1	-8.9
median	3.1
Q3	15.1
95-th percentile	22.1
Maximum	29.1
Range	72.5
Interquartile range (IQR)	24

Descriptive statistics

Standard deviation	13.79384687
Coefficient of variation (CV)	5.537869322
Kurtosis	-1.132189242
Mean	2.490822024
Median Absolute Deviation (MAD)	12
Skewness	-0.1877356196
Sum	1047054.4
Variance	190.2702115
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
17.6	1559	0.4%
17	1519	0.4%
17.2	1490	0.4%
16.8	1483	0.4%
17.3	1455	0.3%
17.1	1445	0.3%
17.8	1440	0.3%
16.2	1429	0.3%
18.2	1426	0.3%
17.5	1409	0.3%
Other values (635)	405710	96.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-43.4	1	< 0.1%
-36	1	< 0.1%
-35.7	1	< 0.1%
-35.5	1	< 0.1%
-35.3	7	< 0.1%

Value	Count	Frequency (%)
29.1	2	< 0.1%
29	1	< 0.1%
28.8	10	< 0.1%
28.7	12	< 0.1%
28.6	2	< 0.1%

RAIN
Real number (ℝ_≥0)

SKEWED
ZEROS

Distinct	253
Distinct (%)	0.1%
Missing	390
Missing (%)	0.1%
Infinite	0
Infinite (%)	0.0%

Mean	0.06447578132
Minimum	0
Maximum	72.5
Zeros	403858
Zeros (%)	96.0%
Memory size	3.2 MiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	0
Maximum	72.5
Range	72.5
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.8210041464
Coefficient of variation (CV)	12.73352768
Kurtosis	1345.506123
Mean	0.06447578132
Median Absolute Deviation (MAD)	0
Skewness	30.04363268
Sum	27104.2
Variance	0.6740478083
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	403858	96.0%
0.1	3722	0.9%
0.2	1841	0.4%
0.3	1382	0.3%
0.4	907	0.2%
0.5	860	0.2%
0.6	702	0.2%
0.7	599	0.1%
0.9	504	0.1%
0.8	488	0.1%
Other values (243)	5515	1.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	403858	96.0%
0.1	3722	0.9%
0.2	1841	0.4%
0.3	1382	0.3%
0.4	907	0.2%

Value	Count	Frequency (%)
72.5	3	< 0.1%
52.1	2	< 0.1%
47.7	1	< 0.1%
46.4	6	< 0.1%
45.9	2	< 0.1%

wd
Categorical

Distinct	16
Distinct (%)	< 0.1%
Missing	1822
Missing (%)	0.4%
Memory size	3.2 MiB

NE	43335
ENE	34142
NW	32600
N	30869
E	29752
Other values (11)	248248

Length

Max length	3
Median length	2
Mean length	2.236314465
Min length	1

Characters and Unicode

Total characters	936895
Distinct characters	4
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	NNW
2nd row	N
3rd row	NNW
4th row	NW
5th row	N

Value	Count	Frequency (%)
NE	43335	10.3%
ENE	34142	8.1%
NW	32600	7.7%
N	30869	7.3%
E	29752	7.1%
SW	28756	6.8%
NNE	28232	6.7%
NNW	25326	6.0%
WNW	24375	5.8%
ESE	24220	5.8%
Other values (6)	117339	27.9%

Histogram of lengths of the category

Value	Count	Frequency (%)
ne	43335	10.3%
ene	34142	8.1%
nw	32600	7.8%
n	30869	7.4%
e	29752	7.1%
sw	28756	6.9%
nne	28232	6.7%
nnw	25326	6.0%
wnw	24375	5.8%
ese	24220	5.8%
Other values (6)	117339	28.0%

Most occurring characters

Value	Count	Frequency (%)
N	272437	29.1%
E	255811	27.3%
W	215638	23.0%
S	193009	20.6%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	936895	100.0%

Most frequent character per category

Value	Count	Frequency (%)
N	272437	29.1%
E	255811	27.3%
W	215638	23.0%
S	193009	20.6%

Most occurring scripts

Value	Count	Frequency (%)
Latin	936895	100.0%

Most frequent character per script

Value	Count	Frequency (%)
N	272437	29.1%
E	255811	27.3%
W	215638	23.0%
S	193009	20.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	936895	100.0%

Most frequent character per block

Value	Count	Frequency (%)
N	272437	29.1%
E	255811	27.3%
W	215638	23.0%
S	193009	20.6%

WSPM
Real number (ℝ_≥0)

ZEROS

Distinct	117
Distinct (%)	< 0.1%
Missing	318
Missing (%)	0.1%
Infinite	0
Infinite (%)	0.0%

Mean	1.729710548
Minimum	0
Maximum	13.2
Zeros	11118
Zeros (%)	2.6%
Memory size	3.2 MiB

Quantile statistics

Minimum	0
5-th percentile	0.3
Q1	0.9
median	1.4
Q3	2.2
95-th percentile	4.3
Maximum	13.2
Range	13.2
Interquartile range (IQR)	1.3

Descriptive statistics

Standard deviation	1.246385565
Coefficient of variation (CV)	0.7205746457
Kurtosis	3.684467043
Mean	1.729710548
Median Absolute Deviation (MAD)	0.6
Skewness	1.625589782
Sum	727256.8
Variance	1.553476978
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1.1	22249	5.3%
1	22150	5.3%
1.2	22141	5.3%
0.9	20955	5.0%
1.3	20383	4.8%
0.8	19110	4.5%
1.4	18523	4.4%
0.7	17543	4.2%
1.5	17019	4.0%
1.6	15793	3.8%
Other values (107)	224584	53.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	11118	2.6%
0.1	4288	1.0%
0.2	4529	1.1%
0.3	2841	0.7%
0.4	7328	1.7%

Value	Count	Frequency (%)
13.2	1	< 0.1%
12.9	1	< 0.1%
12.8	1	< 0.1%
12	1	< 0.1%
11.8	1	< 0.1%

station
Categorical

UNIFORM

Distinct	12
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	3.2 MiB

Aotizhongxin	35064
Shunyi	35064
Gucheng	35064
Wanshouxigong	35064
Wanliu	35064
Other values (7)	245448

Length

Max length	13
Median length	7.5
Mean length	8.416666667
Min length	6

Characters and Unicode

Total characters	3541464
Distinct characters	26
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Aotizhongxin
2nd row	Aotizhongxin
3rd row	Aotizhongxin
4th row	Aotizhongxin
5th row	Aotizhongxin

Value	Count	Frequency (%)
Aotizhongxin	35064	8.3%
Shunyi	35064	8.3%
Gucheng	35064	8.3%
Wanshouxigong	35064	8.3%
Wanliu	35064	8.3%
Dongsi	35064	8.3%
Changping	35064	8.3%
Huairou	35064	8.3%
Dingling	35064	8.3%
Nongzhanguan	35064	8.3%
Other values (2)	70128	16.7%

Histogram of lengths of the category

Value	Count	Frequency (%)
dongsi	35064	8.3%
gucheng	35064	8.3%
aotizhongxin	35064	8.3%
changping	35064	8.3%
tiantan	35064	8.3%
huairou	35064	8.3%
shunyi	35064	8.3%
guanyuan	35064	8.3%
wanliu	35064	8.3%
dingling	35064	8.3%
Other values (2)	70128	16.7%

Most occurring characters

Value	Count	Frequency (%)
n	666216	18.8%
i	385704	10.9%
g	385704	10.9%
a	350640	9.9%
u	315576	8.9%
o	245448	6.9%
h	210384	5.9%
t	70128	2.0%
z	70128	2.0%
x	70128	2.0%
Other values (16)	771408	21.8%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	3120696	88.1%
Uppercase Letter	420768	11.9%

Most frequent character per category

Value	Count	Frequency (%)
n	666216	21.3%
i	385704	12.4%
g	385704	12.4%
a	350640	11.2%
u	315576	10.1%
o	245448	7.9%
h	210384	6.7%
t	70128	2.2%
z	70128	2.2%
x	70128	2.2%
Other values (7)	350640	11.2%

Value	Count	Frequency (%)
D	70128	16.7%
G	70128	16.7%
W	70128	16.7%
A	35064	8.3%
C	35064	8.3%
H	35064	8.3%
N	35064	8.3%
S	35064	8.3%
T	35064	8.3%

Most occurring scripts

Value	Count	Frequency (%)
Latin	3541464	100.0%

Most frequent character per script

Value	Count	Frequency (%)
n	666216	18.8%
i	385704	10.9%
g	385704	10.9%
a	350640	9.9%
u	315576	8.9%
o	245448	6.9%
h	210384	5.9%
t	70128	2.0%
z	70128	2.0%
x	70128	2.0%
Other values (16)	771408	21.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	3541464	100.0%

Most frequent character per block

Value	Count	Frequency (%)
n	666216	18.8%
i	385704	10.9%
g	385704	10.9%
a	350640	9.9%
u	315576	8.9%
o	245448	6.9%
h	210384	5.9%
t	70128	2.0%
z	70128	2.0%
x	70128	2.0%
Other values (16)	771408	21.8%

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

First rows

	df_index	No	year	month	day	hour	PM2.5	PM10	SO2	NO2	CO	O3	TEMP	PRES	DEWP	wd	WSPM	station
0	0	1	2013	3	1	0	4.0	4.0	4.0	7.0	300.0	77.0	-0.7	1023.0	-18.8	NNW	4.4	Aotizhongxin
1	1	2	2013	3	1	1	8.0	8.0	4.0	7.0	300.0	77.0	-1.1	1023.2	-18.2	N	4.7	Aotizhongxin
2	2	3	2013	3	1	2	7.0	7.0	5.0	10.0	300.0	73.0	-1.1	1023.5	-18.2	NNW	5.6	Aotizhongxin
3	3	4	2013	3	1	3	6.0	6.0	11.0	11.0	300.0	72.0	-1.4	1024.5	-19.4	NW	3.1	Aotizhongxin
4	4	5	2013	3	1	4	3.0	3.0	12.0	12.0	300.0	72.0	-2.0	1025.2	-19.5	N	2.0	Aotizhongxin
5	5	6	2013	3	1	5	5.0	5.0	18.0	18.0	400.0	66.0	-2.2	1025.6	-19.6	N	3.7	Aotizhongxin
6	6	7	2013	3	1	6	3.0	3.0	18.0	32.0	500.0	50.0	-2.6	1026.5	-19.1	NNE	2.5	Aotizhongxin
7	7	8	2013	3	1	7	3.0	6.0	19.0	41.0	500.0	43.0	-1.6	1027.4	-19.1	NNW	3.8	Aotizhongxin
8	8	9	2013	3	1	8	3.0	6.0	16.0	43.0	500.0	45.0	0.1	1028.3	-19.2	NNW	4.1	Aotizhongxin
9	9	10	2013	3	1	9	3.0	8.0	12.0	28.0	400.0	59.0	1.2	1028.5	-19.3	N	2.6	Aotizhongxin

Last rows

	df_index	No	year	month	day	hour	PM2.5	PM10	SO2	NO2	CO	O3	TEMP	PRES	DEWP	wd	WSPM	station
420758	35054	35055	2017	2	28	14	3.0	6.0	7.0	5.000000	900.0	82.0	14.6	1013.3	-15.6	N	3.6	Wanshouxigong
420759	35055	35056	2017	2	28	15	11.0	21.0	2.0	5.000000	200.0	45.0	15.4	1013.0	-15.0	NNW	3.3	Wanshouxigong
420760	35056	35057	2017	2	28	16	6.0	20.0	3.0	50.638586	200.0	80.0	14.9	1012.6	-15.4	NW	2.1	Wanshouxigong
420761	35057	35058	2017	2	28	17	11.0	23.0	3.0	12.000000	300.0	87.0	14.2	1012.5	-14.9	NW	3.1	Wanshouxigong
420762	35058	35059	2017	2	28	18	11.0	30.0	2.0	16.000000	300.0	82.0	13.4	1013.0	-15.5	WNW	1.4	Wanshouxigong
420763	35059	35060	2017	2	28	19	11.0	32.0	3.0	24.000000	400.0	72.0	12.5	1013.5	-16.2	NW	2.4	Wanshouxigong
420764	35060	35061	2017	2	28	20	13.0	32.0	3.0	41.000000	500.0	50.0	11.6	1013.6	-15.1	WNW	0.9	Wanshouxigong
420765	35061	35062	2017	2	28	21	14.0	28.0	4.0	38.000000	500.0	54.0	10.8	1014.2	-13.3	NW	1.1	Wanshouxigong
420766	35062	35063	2017	2	28	22	12.0	23.0	4.0	30.000000	400.0	59.0	10.5	1014.4	-12.9	NNW	1.2	Wanshouxigong
420767	35063	35064	2017	2	28	23	13.0	19.0	4.0	38.000000	600.0	49.0	8.6	1014.1	-15.9	NNE	1.3	Wanshouxigong

Overview

Variables

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Interactions

Correlations

Pearson's r

Spearman's ρ

Kendall's τ

Phik (φk)

Cramér's V (φc)

Missing values

Sample

First rows

Last rows